Staff/Principal Full Stack Engineer (Python & React)

Our client builds industrial autonomous vehicle technology. This is a safety-critical, physical-world product — the software you write directly controls autonomous vehicles moving in real industrial facilities.

About the role

As a Staff / Principal Full-Stack Engineer (Python + React) embedded with our client, you will own end-to-end design and delivery of the web-facing and service-layer systems that surround the autonomy stack and the fleet platform.

This role is calibrated for AI-era leveling — the client's engineering team has
shifted its day-to-day workflow so that engineers primarily direct, review, and redirect AI coding agents rather than typing code line-by-line.

The interview bar reflects that shift: evaluation is weighted approximately 70% on system design and systematic thinking and 30% on hands-on coding, with explicit assessment of your ability to oversee AI agent output.

You will be expected to operate as a force multiplier from week one — not just shipping features, but setting architectural direction, drawing hard lines around safety-critical code, and mentoring the broader team on how to work
productively with AI tooling without inheriting its failure modes.

Key Responsibilities:

• Design, build, and maintain production Python backend services (async APIs, data pipelines, integrations with the autonomy stack and the fleet platform) with a relentless focus on reliability, observability, and safetycritical design.
• Deliver React + TypeScript frontends for internal and customer-facing tooling — fleet dashboards, teleoperation consoles, simulation tooling, and operator-facing workflows.
• Direct, review, and correct AI coding agents as a core part of your workflow. Structure prompts and context so agents produce high-quality output; catch and redirect agents when they generate code that is technically correct but architecturally wrong for the use case.
• Own system design decisions end-to-end: surface unknowns, document trade-offs in lightweight ADRs, defend choices under challenge, and adapt designs as constraints evolve.
• Draw explicit boundaries around safety-critical code paths — where AI generated output is acceptable with review, where it must be hand-written, and where additional verification (tests, formal review, staged rollout) is non-negotiable.
• Lead design reviews for new features and architectural changes. Proactively initiate reviews rather than waiting to be asked: "Here's what I'm going to do, here's the plan, here are the trade-offs — what do you think?"
• Work cross-functionally with the client's autonomy, platform, and product teams to translate ambiguous requirements into concrete technical scope.
• Establish production-readiness standards (SLIs / SLOs, idempotency, retry semantics, failure isolation, safe-stop / fail-closed design) and bake them into the services you ship from day one.
• Mentor other engineers on systematic thinking, trade-off reasoning, and AIaugmented workflows.

Qualifications:

• Bachelor's or Master's degree in Computer Science or a closely related field (or equivalent demonstrated experience).
• Deep, hands-on production experience with Python (async frameworks, web / API frameworks, ORM, testing) and React + TypeScript (component architecture, state management with Redux or equivalent, type design). This is not textbook knowledge — we're looking for engineers who have operated these stacks in production under real load.
• Strong fluency with Docker and Kubernetes, and production experience on AWS (or a comparable cloud).
• Demonstrated track record of leading system design at scale: component boundaries, data flow, latency and throughput reasoning, distributedsystems primitives, failure modes, and trade-off analysis across competing priorities (scalability vs. efficiency, consistency vs. availability, latency vs. throughput).
• Active, fluent use of AI coding agents in your day-to-day workflow — prompt and context engineering, rigorous review of AI output, ability to articulate when AI assistance is appropriate and when it isn't. You should be able to describe a specific workflow you use to catch flawed agent output before it reaches production.
• Systematic thinking under pressure: ability to decompose ambiguous problems methodically, engage constructively when your assumptions are challenged, and adapt your approach without simply repeating the original proposal.
• First-principles reasoning: ability to derive answers from fundamental understanding rather than relying exclusively on memorized patterns or frameworks.
• Strong understanding of CI/CD concepts and hands-on experience with related tools (GitHub Actions, GitLab CI, Jenkins, or equivalent).
• Solid foundation in secure API development, data modeling, and front-end performance.
• Excellent written and spoken English. Able to communicate trade-offs crisply, ask the right clarifying questions, and collaborate across distributed teams.
• Able to overlap substantially with US working hours (PT / ET).

Hiring conditions:

• Work remotely from LATAM.
• USD payment - contractor hiring modality.
• Work with world-class global clients.
• Paid time off.